Decomposition Of Technical Efficiency Research Articles

Approximating the influence of external factors on the technical efficiency score of hospital care: evidence from the federal states of Germany

BackgroundA good health care system and, especially, the provision of efficient hospital care are the goals of national and regional health policies. However, the scope of general hospital care in the 16 federal states in Germany varies considerably from region to region. The objectives of this paper are to evaluate the technical efficiencies of all general hospitals of the 16 federal states for the period from 2015 to 2020, to find out the relation between the exogenous factors and score of efficiency, and also the influence of the COVID-19 pandemic on the results of the technical efficiency of hospital care in the German states.MethodsA two-step approach was used. First, an input-oriented Data Envelopment Analysis model with constant returns to scale and variable returns to scale was applied for the 6-year period from 2015 to 2020. The calculation of technical efficiency according to the input-oriented DEA model contains the three components—total technical efficiency (TTE), pure technical efficiency (PTE) and scale efficiency (SE). In the second stage, the influence of exogenous variables on the previously determined technical efficiency was evaluated by applying the tobit regression analysis.ResultsAlthough the level of average technical efficiency of about 90% is high, total technical efficiency deteriorated steadily from 2015 to 2020. Its lowest point at around 78%, was in the year 2020. The deterioration of the average technical efficiency is notably influenced by the lower results in the years 2019 and 2020. The decomposition of technical efficiency also revealed that the deterioration of overall average efficiency was influenced by both pure technical efficiency (PTE) and scale efficiency (SE). Based on the tobit regression analysis performed, it was possible to conclude that the change in the efficiency score can be explained by the influence of exogenous factors only from 6.4% for overall efficiency and from 7.1% for scale efficiency.ConclusionsThe results of the analysis of the overall technical efficiency reveal that the aggregated data of all general hospitals of all 16 federal states show a steadily worsening total technical efficiency every year since 2015. Although, especially, the deterioration of the year 2020 with the occurrence of COVID-19 pandemic, contributes to a deteriorated efficiency average, the deterioration of the efficiency values, based on the analysis performed, is also observable between the years 2016 and 2019. Considering the output generated, for inefficient units and the relevant policy authorities in the hospital sector, it can be recommended that the number of beds and in particular the number of physicians, should be reduced as inputs. Based on this study, it is also recommended that decisions to increase the efficiency of general hospitals should be made with consideration of exogenous factors such as the change in the number of general hospitals or the population density in the respective state, as these had explanatory value in connection with the increase in efficiency values. Due to the wide variation in the size of the federal states, the recommendation is more appropriate for federal states with low population density.

Decomposition of technical efficiency under fixed proportion technologies: an application of data envelopment analysis

Decomposition of technical efficiency under fixed proportion technologies: an application of data envelopment analysis

Decomposition of technical efficiency in agricultural production in Africa into transient and persistent technical efficiency under heterogeneous technologies

Abstract The agricultural sector remains a cornerstone to Africa’s economic transformation and the achievement of the Sustainable Development Goals (SDGs). However, the sector’s performance, in terms of productivity growth, has been sub-optimal when compared with performances in Asia, America, and Europe. Technical efficiency is a major contributor to the growth in agricultural productivity. However, there is limited research about the sources of technical inefficiency in agricultural production in Africa. This is critical given that Africa has problems with food security and high poverty. This study applied a parametric technique to estimate technical efficiency in Africa’s agricultural sector under heterogeneous technologies, while separating unobserved country-specific heterogeneities from transient and persistent technical efficiency. Data consisted of 49 African countries spanning from 1990 to 2016. Assuming a homogeneous technology, the estimated mean technical efficiency of 38.2%, suggests that, in Africa, about 62% of the potential agricultural output is untapped. However, considering heterogeneity in production technologies, the mean estimated technical efficiency value differed between the two classes. The numbers suggest that about 59% and 69% of untapped potential agricultural output in class one and class two groups, respectively. In all cases, persistent technical inefficiency hinders technical efficiency, an indication that government or regional agricultural policies should be long-term oriented. With the evidence of conditional convergence in technical efficiency, efforts to improve persistent technical efficiency can drive regional targets in food security and poverty alleviation and induce inclusive growth and sustainable development.

Decomposing technical inefficiency using the principle of least action

In for-profit organizations, profit efficiency decomposition is considered important since estimates on profit drivers are of practical use to managers in their decision making. Profit efficiency is traditionally due to two sources – technical efficiency and allocative efficiency. The contribution of this paper is a novel decomposition of technical efficiency that could be more practical to use if the firm under evaluation really wants to achieve technical efficiency as soon as possible. For this purpose, we show how a new version of the Measure of Inefficiency Proportions (MIP), which seeks the minimization of the total technical effort by the assessed firm, is a lower bound of the value of technical inefficiency associated with the directional distance function. The targets provided by the new MIP could be beneficial for firms since it specifies how firms may become technically efficient simply by decreasing one input or increasing one output, suggesting that each firm should focus its effort on a specific dimension (input or output). This approach is operationalized in a data envelopment analysis framework and applied to a dataset of airlines.

Investigating health system performance: an application of data envelopment analysis to Zambian hospitals.

BackgroundZambia has recently articulated an ambitious national health program designed to meeting health-related MDGs. Public expectations are high and Zambia continues to receive significant resources from global and bilateral donors to support its health agenda. Although the lack of adequate resources presents the most important constraint, the efficiency with which available resources are being utilised is another challenge that cannot be overlooked. Inefficiency in producing health care undermines the service coverage potential of the health system. This paper estimates the technical efficiency of a sample of hospitals in Zambia.MethodsEfficiency is measured using a DEA model. Vectors of hospital inputs and outputs, representing hospital expended resources and output profiles respectively, were specified and measured. The data were gathered from a sample of 30 hospitals throughout Zambia. The model estimates an efficiency score for each hospital. A decomposition of technical efficiency into scale and congestion is also provided.ResultsResults show that overall Zambian hospitals are operating at 67% level of efficiency, implying that significant resources are being wasted. Only 40% of hospitals were efficient in relative terms. The study further reveals that the size of hospitals is a major source of inefficiency. Input congestion is also found to be a source of hospital inefficiency.ConclusionThis study has demonstrated that inefficiency of resource use in hospitals is significant. Policy attention is drawn to unsuitable hospital scale of operation and low productivity of some inputs as factors that reinforce each other to make Zambian hospitals technically inefficient at producing and delivering services. It is argued that such evidence of substantial inefficiency would undermine Zambia's prospects of achieving its health goals.

Estimation and decomposition of technical efficiency for sugarbeet farms

This study computes technical efficiency for Idaho sugarbeet farms and decomposes it into pure technical efficiency, scale efficiency, and congestion efficiency using nonparametric procedures. The results indicate that the average efficiency is 0.88 with 45% of the farms in the sample exhibiting full efficiency. Improper scale operation and input overutilization are the major sources of inefficiency for remaining farms. Technical efficiency is independent of farm size. A Tobit model was used to examine the impacts of variables such as farm size, specialization, tenancy position, hired labour, location, and managerial ability on efficiency. Inefficiency in sugarbeet production results in a shortfall of potential revenues not only for producers, but also for landlords and processors.